STABLE DIFFUSION - Tone Mapping Miracle Might Move Mountains - Playing with the CFG Scale in ComfyUI

Pixovert
7 Aug 202305:45

TLDRThe speaker shares insights on using the CFG scale in stable Fusion within a comfy UI. They discuss the challenges and a discovered method to overcome issues with high CFG values, leading to the creation of diverse and vibrant images. The modification is based on research from ByteDance, addressing flaws in stable diffusion's noise schedule. The speaker invites users to learn more through their updated course, which covers prompt engineering, CFG, and their interactions.

Takeaways

  • 🔍 The speaker was researching the course on ComfyUI and Stable Fusion and discovered interesting aspects of the Classifier Free Guidance (CFG) scale.
  • 🌟 The CFG scale's behavior and its impact on the quality of generated images was a focal point of the research.
  • 💡 The speaker found a way to address issues with the CFG scale by modifying its application between the sampler and the model.
  • 🎨 The results showcased a variety of images generated from the same prompt, demonstrating the versatility of the method.
  • ⚙️ The modification is based on research from ByteDance, addressing the stable diffusion's flawed noise schedule in sample steps.
  • 🚀 The speaker experimented with two samplers, achieving a remarkable contrast in the final images.
  • 💥 The CFG scale typically breaks down at high levels, but the modification allowed for continued functionality and impressive results.
  • 📝 The original goal was to make the CFG respect the prompt more, but the speaker shifted focus to experimenting with the CFG scale itself.
  • 🎓 The speaker offers a course that covers topics like prompts, CFGs, and their interactions, which has been recently updated with new content.
  • 🔗 A discount is available for those interested in the course, which includes a specific lecture on CFG, prompts, clip skipping, and sample steps.
  • 🌐 The technology is still in its experimental phase and not yet ready for professional use, but the potential is promising.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is the discovery and exploration of the CFG scale in the context of a ComfyUI and Stable Fusion, and how it can be improved to produce better results.

  • What does the CFG scale stand for?

    -The CFG scale stands for Classifier Free Guidance scale, which is a parameter that influences the behavior of AI models like Stable Fusion.

  • What was the initial problem with the CFG scale?

    -The initial problem with the CFG scale was that it would produce broken and unusable results at higher levels, specifically around 15 or 16, and became completely unworkable by the time it reached 30.

  • How did the modification to the CFG scale improve the results?

    -The modification introduced a simple basic modifier that goes between the model and the sampler, changing the behavior of the sampler. This allowed for the production of more vibrant and varied images without the negative effects typically associated with high CFG values.

  • What is the source of the research that led to the modification of the CFG scale?

    -The research that led to the modification of the CFG scale comes from ByteDance, where researchers discovered interesting aspects of the mathematics inside stable diffusion and proposed solutions to improve it.

  • What was the original intention of the speaker when working with the CFG scale?

    -The speaker originally intended to make the CFG scale respect the prompt more, using it more effectively. The prompt was a piece of text about the loss of humanity to AI.

  • How did the speaker's approach change during the research?

    -The speaker decided to stop focusing on making the CFG scale respect the prompt and instead started playing with the CFG scale itself, which led to the discovery of the improved results.

  • What is the current status of the modification to the CFG scale?

    -The modification is currently in an experimental phase and not yet available for professional use. However, the speaker mentions that an extension might be released in the future.

  • How can one learn more about the CFG scale and related topics?

    -The speaker offers a course where these topics are discussed in detail, including a new section on prompt engineering, CFG, clip skipping, sample steps, and their interactions.

  • What is the main takeaway from the video for someone interested in AI and Stable Fusion?

    -The main takeaway is that modifications to the CFG scale can significantly improve the output of AI models like Stable Fusion, leading to more vibrant and varied images without the negative effects of high CFG values.

  • Are there any other proposals for fixing the CFG scale mentioned in the video?

    -The speaker mentions that there are a couple of different proposals for fixing the CFG scale, but does not go into detail about them in the video.

Outlines

00:00

🤔 Exploration of CFG Scale and Its Impact on AI-Generated Images

The speaker discusses their research into a comfortable user interface (UI) and stable Fusion, during which they stumbled upon various intriguing aspects. A key focus was the Classifier Free Guidance (CFG) scale's behavior, its effectiveness, and limitations. They found that certain modifications to the CFG could enhance the results, as demonstrated by a variety of images generated from the same prompt but with different seeds. The speaker particularly marvels at the images produced by combining two samplers, which resulted in a striking contrast and unprecedented visual outcomes. Initially, they struggled with the CFG's intended function, which was to make it respect the prompt more. However, by playing with the CFG scale, they uncovered fascinating results. The modifications are based on research from ByteDance, addressing issues in stable diffusion and its noise schedule. The speaker emphasizes the novelty of this research, recently published in a paper, and mentions an updated course where these topics are explored in-depth, including prompt engineering and the interplay between CFG, prompts, and other elements.

05:00

🚀 New Developments in CFG and Prompt Engineering

Continuing from the previous discussion, the speaker invites the audience to join their course to delve deeper into the intricacies of CFG, prompt clip skipping, and sample steps. A specific lecture is highlighted that focuses on the interaction between these elements. The speaker expresses excitement about the potential of this new technology and shares that there are multiple proposals to fix the CFG. They encourage the audience to use a discount code to access the course and anticipate the release of the extension, which is currently in its experimental phase.

Mindmap

Keywords

💡Stable Diffusion

Stable Diffusion is a term used in the context of AI and machine learning, referring to a specific type of generative model that creates new images or artifacts based on given input data. In the video, the speaker is discussing their research and findings related to Stable Diffusion, particularly focusing on the improvements and modifications to the system that can enhance the quality and variety of the generated images.

💡ComfyUI

ComfyUI seems to be a user interface or a platform that the speaker is using for their research on Stable Diffusion. It is implied that this interface is designed to make the process of working with AI models more comfortable or intuitive, possibly with a focus on image generation and manipulation.

💡CFG Scale

CFG stands for Classifier Free Guidance, a method used in AI models like Stable Diffusion to guide the generation process towards certain desired outcomes. The scale refers to the level or intensity of this guidance that is applied during the image generation process. In the video, the speaker discusses their findings about how adjusting the CFG Scale can lead to different results and how they managed to overcome some of its limitations.

💡Tone Mapping

Tone mapping is a technique used in image processing to adjust the contrast and color balance of an image to make it more visually appealing or to better represent the scene. In the context of the video, the speaker discovered that by using tone mapping, they could modify the behavior of the sampler in the Stable Diffusion process, leading to improved image results.

💡Miracle

In the context of the video, 'Miracle' is used metaphorically to describe the surprising and positive outcomes that the speaker achieved by experimenting with the CFG Scale and tone mapping in Stable Diffusion. It implies that the results were unexpected and almost unbelievable in their quality and variety.

💡Might Move Mountains

This phrase is used figuratively to suggest that the speaker's discoveries and modifications to the CFG Scale in Stable Diffusion have the potential to bring about significant changes or improvements in the field of AI image generation. It conveys a sense of the magnitude of the impact that these findings could have.

💡Variety

In the video, 'Variety' refers to the range of different images that can be generated using the same prompt but with different seeds in the Stable Diffusion process. The speaker is impressed by the diverse outcomes that can be achieved, which was one of the positive results of their experimentation with the CFG Scale and tone mapping.

💡God Rays

God Rays is a term used to describe a specific visual effect often seen in images or photographs, where beams of light appear to radiate from a bright source, such as the sun, creating a dramatic and visually striking effect. In the video, the speaker is particularly fond of one image that features this effect, indicating their appreciation for the aesthetic quality of the images generated by the modified Stable Diffusion process.

💡Prompt

In the context of AI and machine learning, a 'Prompt' is the input data or information given to the system to guide the output. In the video, the speaker initially had a specific prompt related to the 'loss of humanity to AI,' but later decided to focus more on experimenting with the CFG Scale and its effects on image generation rather than the content of the prompt itself.

💡Research

Research in this context refers to the investigation and study conducted by the speaker and other experts in the field to improve the Stable Diffusion process. The speaker mentions research from 'bite dance' (likely a reference to ByteDance, the company behind TikTok), which provided insights and solutions for the issues with the CFG Scale.

Highlights

Discovered interesting behaviors of the CFG scale in ComfyUI and Stable Fusion research.

The Classifier Free Guidance (CFG) scale sometimes works well and sometimes doesn't.

There are ways to fix problems with CFG and improve the results.

All images shown use the exact same prompt, demonstrating variability.

The variety of images produced is stunning, with one featuring god rays.

The CFG scale typically breaks around level 15-16 in ComfyUI.

A modification to the CFG scale allows for better contrast and new image creations.

Two samplers with the modified CFG scale produce amazing contrast in images.

The modification is a simple basic modifier based on research from ByteDance.

Stable diffusion uses a flawed noise schedule in sample steps.

The modification avoids negative effects of high CFGs while maintaining vibrant colors.

The research paper on this modification was published recently.

An extension based on this research is in the experimental phase.

A course on ComfyUI and Stable Fusion discusses CFG, prompts, and their interactions.

The course has been updated with a new section on prompt engineering.

A discount is available for those interested in the course.

There are different proposals for fixing the CFG, with promising early results.

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